https://github.com/openrobotlab/pointllm
공식 코드PointLLM: Empowering Large Language Models to Understand Point Clouds
Papers with Code 아카이브
Generative 3D Object Classification
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The task of generative 3D object classification involves prompting the model to generate the object type from its point cloud, distinguishing it from discriminative models that directly classify objects based on probability comparisons.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/qizekun/ShapeLLM
공식 코드ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
https://github.com/tangyuan96/minigpt-3d
공식 코드MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors
https://github.com/ziyuguo99/point-bind_point-llm
공식 코드https://github.com/Pointcept/GPT4Point
https://github.com/Yui010206/CREMA
https://github.com/qizekun/ReCon
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
https://github.com/runpeidong/act
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
https://github.com/umass-foundation-model/3d-llm
https://github.com/zrrskywalker/point-bind
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.